= +  RTV(f), 
where \(X\)  is the stylized image and \(\theta \)  parameterizes the spatial deformation. Hyperparameters \(\alpha \)  and \(\beta \)  control the relative importance of content preservation and spatial deformation to stylization. Hyperparameter \(\gamma \)  controls the amount of regularization on the spatial deformation. The effect of varying \(\alpha \)  is analyzed in [1]}, [2]}. The effect of changing \(\beta \)  and \(\gamma \)  is illustrated in Figure REF . We use standard iterative techniques such as stochastic gradient descent or L-BFGS to minimize Eq. (REF ) with respect to \(O\)  and \(\theta \) . Our implementation of DST can be found at https://github.com/sunniesuhyoung/DST.
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